14 - 16 July 2022

Barcelona MMSML Workshop

METHODS IN MOLECULAR SIMULATIONS AND MACHINE LEARNING


On site — Barcelona Biomedical Research Park

A three-day get together of discussions, activities and short talks

Molecular simulations are changing. converging quantum and classical simulations, accurate machine learning potentials for richer physics, chemical representations and quantum computers. THIS WORKSHOP is about shaping this future.

Speakers

Rafael Gómez-Bombarelli

MIT, USA

John Chodera

MSKCC, USA

Peter Eastman

U. Stanford, USA

Gianni
De Fabritiis

UPF, Spain

Cecilia Clementi

FU Berlin, Germany

Raimondas Galvelis

Acellera, Spain

Paolo Carloni

Jülich Research Center, Germany

Chris Chipot

U. Lorraine and U. Illinois, Urbana-Champaign, USA

Kristof T. Schütt

TU Berlin, Germany

Michael Gastegger

TU Berlin, Germany

Olexandr Isayev

Carnegie Mellon University, USA

​ Loche Philip Robin

EPFL, Switzerland

Elizabeth Decolvenaere

D.E. Shaw Research, USA

Matthias Rupp

U. Konstanz, Germany

Olga Kononova

Roivant, USA

Alexander Wade

U. College London, UK

Tristan Bereau

UvA, Netherlands

Tess
Smidt

MIT, USA

Julien
Michel

U. Edinburgh, UK

Jonathan Godwin

DeepMind, UK

Frank
Noe

FU Berlin, Germany

Hanwen Zhang

University of Oxford, UK

Justin
Smith

Nvidia, USA

Gábor
Csányi

University of Cambridge, UK

Rianne van den Berg

Microsoft Research, Netherlands

Robin
Winter

Bayer
Germany

Daniel
Cole

Newcastle University, UK

Jose
Jimenez

Microsoft Research, UK

Luis Itza Vazquez-Salazar

University Basel, Switzerland

Ryota Tomioka

Microsoft Research, UK

Research topics

  • How to develop new ML potentials in the context of physics-based molecular modelling and simulations.

  • What software infrastructure is required to support hybrid ML- and physics-based simulations.

  • How to handle charges and long-range interactions.

  • How to extend machine learning potentials to charge transfer and reactions.

  • How to optimize neural network calculations, latency, CUDA graphs, tensor cores.

  • What is the role of quantum computers and special hardware in quantum chemistry.

Description

Nature and the fundamental equations that govern physics at atomistic scales are well understood, i.e. quantum mechanics and the Schrodinger equation. However, solving such equations is possible only for very simple systems such as the hydrogen atom. While advances have been made by using a quantum computer, the field of quantum chemistry is devoted to finding approximations for solving the quantum problem on classical computers but even these approximations remain slow for biological applications and inaccurate in certain conditions.

Machine learning potentials, as universal many-body function approximators, might be capable of delivering the next generation of force fields when used together with physics-based potentials, blurring the boundary between quantum mechanics, molecular mechanics and coarse-grained simulations into a cohesive methodology.

In recent years, incredible progress has been made in transferable molecular representations which can learn effective potential functions. New methods for learning such potentials and even the energetics of the underlying physical systems are now available. Applications using differentiable molecular simulations offer a further way to create force-fields. The possibility to have molecular mechanics simulations with changing molecular identity seems now reachable as well as reactivity. However, there are still problems in extending the generalizability of such potentials, lack of accurate datasets, handling of charges and charged molecules, all within a speed bound which must be able to handle large systems like protein complexes. This workshop is expected to get us together to discuss and advance these scientific problems towards next generation molecular simulations.

The Venue

Barcelona Biomedical Research Park

C/Doctor Aiguader, 88
E-08003 Barcelona, Spain

The meeting will be held at the Barcelona Biomedical Research Park (PRBB), a large scientific hub that brings together several research centres to promote research in the field of life sciences, human health, and biomedicine.

Organizers and Contacts

CompBioMed

The MMSML Workshop is organized as part of the training activities of CompBioMed2, a European Commission H2020 funded Centre of Excellence focused on the use and development of computational methods for biomedical applications.

Comprising members from academia, industry and the healthcare sector, CompBioMed2 has established itself as a hub for practitioners in the field, successfully nucleating a substantial body of research, education, training, innovation and outreach within the nascent field of Computational Biomedicine.